Abstract
Abstract It is often thought that regression data should be mean-centered before being diagnosed for collinearity (ill conditioning). This view is shown not generally to be correct. Such centering can mask elements of ill conditioning and produce meaningless and misleading collinearity diagnostics. In order to assess conditioning meaningfully, the data must be in a form that possesses structural interpretability.
Keywords
CollinearityInterpretabilityConditioningStatisticsEconometricsMathematicsComputer scienceArtificial intelligence
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Publication Info
- Year
- 1984
- Type
- article
- Volume
- 38
- Issue
- 2
- Pages
- 73-77
- Citations
- 127
- Access
- Closed
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Cite This
David A. Belsley
(1984).
Demeaning Conditioning Diagnostics through Centering.
The American Statistician
, 38
(2)
, 73-77.
https://doi.org/10.1080/00031305.1984.10483169
Identifiers
- DOI
- 10.1080/00031305.1984.10483169